Continuous Intelligent Validation (cIV)

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Get detailed overview

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cIV simplifies and automates GxP-compliant software validation with cutting-edge AI

cIV is an AI-enabled Continuous Validation platform designed to streamline and automate GxP-compliant software validation.

Built on advanced AI models, cIV delivers efficiency, accuracy, and speed in three key areas:

• Transform your already available knowledge base (e.g. manuals) into structured, GxP-compliant URS. cIV’s language models ensure critical requirements are consistently captured and accurately formatted.
• Leverage retrieval-augmented generation (RAG) to create comprehensive test cases derived from the URS. Each test case is contextually relevant, regulatory-compliant, and packaged for seamless automation, guaranteeing robust test coverage.
• cIV executes tests utilizing autonomous agents. Validates requirements, captures audit trails, and generates traceable test evidence, including screenshots and logs.

Why cIV?

• Structured Compliance: Automatically generate URS and test cases tailored to GxP standards.
• Efficient Execution: Automate test runs with precise validation and traceable evidence.
• Centralized Monitoring: Stay informed with an integrated dashboard for managing tasks and reviewing outcomes.
• Scalability: Adapt seamlessly to changing requirements with cIV’s flexible architecture. Your software changes, then cIV adapts using its self-healing feature.

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cIV's AI features include:

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Automated URS Generation

Advanced language models transform manuals and specifications into structured, GxP-compliant URS documents, significantly reducing manual effort and errors.

Intelligent Test Case Creation with Full Traceability

Using retrieval-augmented generation (RAG), AI automatically creates detailed test cases from URS documents. Each test case links back to the original requirement, ensuring regulatory compliance and simplifying audits.

Adaptive Learning for Evolving Validation Needs

AI agents learn from historical validation data and user interactions, adapting to new software features and improving validation accuracy over time.

Autonomous Test Execution & Evidence Capture

AI-driven agents execute tests autonomously, generating audit-ready outputs such as screenshots, execution logs, and traceability matrices—ensuring transparency and comprehensive documentation.